Current Publications
Dynamic responses of wind turbines under unwaked and waked conditions
Muhammad Rubayat Bin Shahadat, Zhenyu You, Shuolin Xiao, Yu Huang, Benjamin Schafer, Yangyang Chen, Charles Meneveau, Zheng Li
Accurate prediction of dynamic responses of wind turbines under multi-scale, time-varying, realistic atmospheric conditions remains a major challenge, particularly for turbines operating inside the wake of upstream turbines. Most of the existing studies rely on idealized inflow or simplified aerodynamic loadings that fail to fully capture the spatiotemporal variability of atmospheric turbulence. To understand the dynamic responses of the wind turbines under realistic atmospheric conditions, in this study, we employ data from a large-scale physical modela large-eddy simulation (LES) of a wind farm during a 24-h diurnal cycle and perform structural dynamic analyses over two illustrative wind turbines. Leveraging the data-access tools from the Johns Hopkins Turbulence Database - Wind (JHTDB-Wind) database, we extract the time-resolved aerodynamic loads from the first and third rows of the wind farm, where the turbine from the first row represents the unwaked turbine and the turbine from the third row represents the turbine under wake conditions. Three distinct operating regimes (high, medium, and low power generation) are identified within the diurnal cycle and analyzed separately to capture the influence of atmospheric stability and turbulence intensity on the dynamic responses of wind turbines. Using these LES-based unsteady loads, we perform detailed 3D finite-element simulations of the NREL 5 MW blade to quantify tip deflection and stress distribution. Our results show that wake turbulence enhances dynamic fluctuations, leading to higher dynamic tip deflection and stress amplitudes. We have also developed a reduced order one-dimensional (1D) beam model capable of reproducing the blade's primary bending response and validated it against our 3D FEM results. By integrating large-scale atmospheric simulation data with detailed 3D structural modeling, this study provides a scalable pathway toward fully coupled LES, enabling computationally efficient aeroelastic modeling at wind-farm scale.
Comprehensive Numerical and Experimental Investigations on Endolaryngeal Mobilization
Weibing Cai, Azure Wilson, Guofeng He, Elizabeth Hary, Ivan Tkac, Stephanie Misono, LeaSayce, and Zheng Li
Objective: To evaluate how subperichondrial mobilization affects implant- tissue mechanics, glottal configuration, and vibra tory behavior in computational simulations of medialization laryngoplasty (ML).
Methods: We used a finite- discrete element method (FDEM) framework to simulate subperichondrial tissue- cartilage separa tion and implant insertion in laryngeal models reconstructed from high- resolution magnetic resonance imaging. Four dissec tion conditions were evaluated, ranging from no mobilization to increasing dissection length distal to the thyroplasty window. Outcome measures included change in glottal area, vocal fold medial displacement, finite element fracturing along the tissue- cartilage interface, and estimated vibratory frequency.
Results: Increasing dissection length produced increased medial displacement, progressive reductions in glottal area, fewer secondary extensions of the dissection plane during implantation, and higher estimated vibratory frequencies (range: 100.4 120.8 Hz). These findings indicate that subperichondrial tissue mobilization alters implant- induced force transmission and mod ifies boundary conditions relevant to vibration.
Conclusion: In this first application of FDEM to simulate laryngeal biomechanics in ML, subperichondrial dissection length demonstrated direct effects on model predictions relevant to implant sizing, placement strategy, and anticipated phonatory out comes. Incorporating tissue mobilization into computational frameworks as a mechanically meaningful variable improves phys iological realism and supports future development of subject- specific surgical planning tools.
Level of Evidence: Level V. This study provides preclinical computational evidence using FDEM, supporting and extending clinical observations in ML.
Gradient-Driven Physics Informed Neural Networks for Conduction Heat Transfer and Incompressible Laminar Flow
Tingying Lu, M. R. B. Shahadat, Qilin Liu, Runlin He, Xiaoyu Jiang, and Zheng Li
partial differential equations (PDEs) by embedding physical laws directly into the learning process. However, despite their flexibility, traditional PINNs often struggle to capture sharp gradients and intricate solution features, which limits their effectiveness in many practical problems. In this work, we have introduced Gradient-Driven Physics-Informed Neural Networks (GDPINNs) that improve the ability of traditional PINNs to resolve sharp gradients. By incorporating gradient information directly into the loss function, GDPINNs better target regions where traditional PINNs typically fail. We validated the method on steady-state and transient heat conduction problems, including a central heating source and a sinusoidal boundary condition, and found strong agreement with reference solutions. To further understand the framework’s capability, we applied it to a high-gradient steady-state and transient heat conduction problem, where GDPINNs show clear advantages over traditional PINNs and align closely with reference results. We also extended GDPINNs to incompressible laminar flow in a lid-driven cavity, demonstrating its broader applicability. In these cases, GDPINNs consistently provide higher accuracy and better capture critical solution features, highlighting their potential to improve PINNs-based approaches for complex physical problems with sharp gradients.
Fluid–structure interaction simulations to investigate the asymmetrical pattern and energy transfer during vocal fold vibrations
Guofeng He, Qilin Liu, Weibing Cai, Azure Wilson, Mohammad Hossein Doranehard, LeaSayce, Haoxiang Luo, and Zheng Li
Asymmetrical vocal fold vibration is the cause of many voice problems. In this study, a two-dimensional fluid–structure interaction model is developed with the finite element method in COMSOL Multiphysics. The vocal folds with asymmetric stiffness are simulated and compared with the symmetric vocal folds as well as unilateral immobile vocal folds. The vocal fold vibration pattern and energy exchange between the fluid and vocal fold structure are analyzed. The results show that the unilateral vocal fold paralysis (UVFP) and the stiffness difference between the two vocal folds would lead to a decrease in the vibration amplitude compared with symmetrical conditions. The asymmetrical vocal fold vibration allows a frequency lock-in between two sides of the vocal fold, and the lock-in frequency is sensitive to the vocal fold stiff ness. The vocal fold vibration can maintain a quasi-periodic pattern when the stiffness difference is less than 5MPa. 10MPa stiffness differ ence can trigger a transition from the quasi-periodic state to the chaotic state. The energy conversion efficiency between fluid and structure is reduced in the presence of a stiffness difference and under UVFP conditions. This efficiency is further decreased when chaotic vibration hap pens, indicating the importance of vibration regularity in maintaining effective fluid-to-structure energy transfer.
Acoustic properties of symmetric and asymmetric vocal fold vibration
Qilin Liu, GuofengHe, LeaSayce, HaoxiangLuo, and ZhengLi
To investigate the acoustic properties of signals generated by symmetric and asymmetric vocal fold vibrations, a flow-acoustic splitting method is employed to model the glottal airflow associated with voice production. The perturbed compressible pressure, p0, is calculated by the linearized perturbed compressible equations (LPCE). Based on p0 and the source term of the LPCE, acoustic behavior related to the medial thickness of the vocal fold and the frequency difference between the two sides of the vocal fold are analyzed. The results show that the opposite-polarity source pair is responsible for the production of p0 and the opposite-polarity source pair is located right at the entrance of the glottal gap. The frequency difference of the two sides diminishes the opposite-polarity source pair and causes amplitude modulation of p0. Consequently, asymmetric vibration can lead to voice problems. The increase in the medial thickness makes the distribution of the paired sources more compact and stronger, and it enhances the intensity ratio between the p0 and the hydrodynamic pressure variation, thereby pos itively contributing to voice production.
An airfoil-based synthetic actuator disk model for wind turbine aerodynamic and structural analysis
Muhammad Rubayat Bin Shahadat, Mohammad Hossein Doranehgard, Weibing Cai,
Charles Meneveau, Benjamin Schafer, Zheng Li
This study introduces an airfoil-based refinement technique to enhance the Actuator Disk Model (ADM) for improved wind turbine aerodynamic load prediction and structural simulation in conjunction with Large Eddy Simulations of the wind flow. While ADM offers higher computational efficiency than the more detailed but resource-intensive Actuator Line Model (ALM), it traditionally lacks the resolution needed to capture the localized blade forces accurately. To address this limitation, we introduce a refinement technique that uses airfoil-specific data and employs interpolation-based grid point refinement, achieving ALM-comparable accuracy while preserving ADM’s efficiency. Unlike conventional ADM that provides only rotor-disk averaged forces, our synthetic method tracks transient aerodynamic load variations over multiple blade revolutions, allowing us to calculate the distributions of maximum and minimum loads during typical cycles. Applied to the NREL 5 MW reference turbine, our enhanced ADM accurately predicts key aerodynamic parameters (angle of attack, axial velocity, lift, drag, axial and tangential forces along the blades) as well as structural responses (blade tip deflection, maximum stress, and stress concentration). Our results show that the tip deflection ranges from 2.33m (3.69 % of blade length) to 4.28m (6.79 %), with maximum stress concentration occurring near the blade root. This research demonstrates that a refined synthetic ADM approach can serve as a computationally efficient alternative for both aerodynamic analysis and structural simulation of wind turbine blades subjected to realistic wind fields.
Large eddy simulation of wind farm performance in horizontally and vertically staggered layouts
Muhammad Rubayat Bin Shahadat, Mohammad Hossein Doranehgard, Weibing Cai, Zheng Li
This numerical investigation employs Large Eddy Simulation (LES) coupled with Actuator Disk Model (ADM) to evaluate wind farm layout optimization strategies. The study presents a systematic analysis of aligned, horizontal staggering, vertical staggering, and mixed (combination of horizontal and vertical) staggering configurations, aiming to establish optimal design parameters for enhanced power production. The investigation examines key performance metrics including mean velocity distributions, turbulence intensity characteristics, and power generation efficiency. Results demonstrate better performance of both horizontal and vertical staggering patterns compared to conventional aligned configurations, with horizontal staggering exhibiting notably higher power output than vertical arrangements. Our findings also suggest that mixed configurations, incorporating both horizontal and vertical staggering, can offer optimal performance characteristics. This research advances the understanding of wake interactions in complex wind farm layouts and provides design guidelines for maximizing wind farm power generation efficiency through strategic turbine positioning.
Comparative analysis of drug deposition patterns among three commercial nasal spray brands: A computational and experimental study
Guiliang Liu, Mohammad Hossein Doranehgard, Xuan Ruan, Bingkai Chen, Brent Senior, Adam Kimple, Rui Ni, Zheng Li
This study investigates drug deposition patterns in nasal drug delivery by combining experimental measurements with computational fluid dynamics simulations. We analyzed three, over the counter, mometasone nasal spray devices, experimentally characterizing particle diameter (dp), spray velocity (up), and spray angle (α). Unlike previous studies that relied on assumed parameters or single-brand analyses, we conducted comparative analyses using measured parameters integrated into COMSOL Multiphysics simulations. The study optimized the Line of Sight (LOS) method by exploring various spray positions and instructions to avoid anterior loss of medication in the anterior nasal cavity. Results revealed that Brand 3, with its narrow spray angle, achieved superior drug delivery efficiency when properly aligned with the target region. However, its performance decreased significantly when misaligned due to its smaller spray cone angle. Our findings show that sprays with narrower cone angles delivered medicine more effectively to the ostiomeatal complex (OMC) with up to 44% higher efficiency using the LOS method. Additionally, in cases with septal deviation, we observed a 14–20% higher drug deposition rate in the right nasal cavity compared to the left. The LOS method significantly improved drug deposition by 2.86–3 times, while the Deep Spray method further enhanced it by 38–50%. This integrated experimental-computational approach provides practical insights for optimizing nasal spray device design and administration techniques, particularly considering anatomical variations.
Computational Modeling of Nasal Cavity Aerodynamics: Implications for Surgical Outcomes and Targeted Drug Administration
Guiliang Liu, W. Jared Martin, Yasine Mirmozaffari, Rui Ni, and Zheng Li
The primary goal of sinonasal surgery is to improve a patient’s quality of life, which is generally achieved by enhancing drug delivery (eg, saline rinses, nasal steroids) and nasal airflow. Both drug delivery and nasal airflow are dependent on the anatomic structure of the sinonasal cavity and the relationship between this anatomy and airflow and drug delivery can be studied using computational fluid dynamics (CFD). CFD generally uses computed tomography scans and computational algorithms to predict airflow or drug delivery and can help us understand surgical outcomes and optimize drug delivery for patients. This study employs CFD to simulate nasal airflow dynamics and optimize drug delivery in the nasal cavity to highlight the utility of CFD for studying sinonasal disease. Utilizing COMSOL Multiphysics software, we developed detailed models to analyze changes in airflow characteristics before and after functional endoscopic sinus surgery, focusing on pressure distribution, velocity profiles, streamline patterns, and heat transfer. This research examines the impact of varying levels of nasal airway obstruction on airflow and heat transfer. In addition, we explore the characteristics of nasal drug delivery by simulating diverse spray parameters, including particle size, spray angle, and velocity. Our comprehensive approach allows for the visualization of drug particle trajectories and deposition patterns, providing crucial insights for enhancing surgical outcomes and improving targeted drug administration. By integrating patient-specific nasal cavity models and considering factors such as airway outlet pressure, this study offers valuable data on pressure cross-sections, flow rate variations, and particle behavior within the nasal passages. The findings of this research can be useful for both surgical planning and the development of more effective nasal drug delivery methods, potentially leading to enhanced clinical outcomes in respiratory treatment.